G protein-coupled receptors (GPCRs) are abundant membrane proteins of extreme pharmacological importance since they are the primary targets for about 30% of prescription drugs that are currently on the market, and are likely to be potential targets for new therapeutic agents. Despite a great deal of research activity in the GPCR field, the design of powerful drugs acting at these receptors has lagged behind due to the limited understanding of the ligand-induced conformational changes of these receptors associated with specific physiological functions. For years, conventional drug design at GPCRs has mainly focused on the inhibition of a single receptor at a usually well-defined ligand-binding site. The growing body of evidence that GPCRs form clinically relevant dimers/oligomers with implications in several disorders has recently added a new complexity to the field, making the understanding of the mechanisms and dynamics governing the interaction between receptor pairs and/or higher-order oligomers equally important for successful rational drug design. The wealth of new higher-resolution structural, biochemical, and biophysical information on GPCRs that has appeared in the recent literature, coupled to recent advancements in coarse-grained modeling and enhanced sampling algorithms, suggests new ways to efficiently explore the conformational space of GPCRs (both monomers and dimers/oligomers), and to generate novel testable hypotheses of molecular mechanisms underlying receptor function. In this grant application, we propose to conduct exploratory metadynamics-based computational studies of ideal membrane protein systems, i.e. [unreadable]-adrenergic receptor, glycophorin A, and the transmembrane domain dimer of the amyloid precursor protein, to validate the efficiency of enhanced sampling methods in predicting ligand-specific activated states and/or dimerization-disrupting mutants that agree with experimental data. PUBLIC HEALTH RELEVANCE: The discovery of powerful therapeutic drugs acting at G-protein coupled receptors (GPCRs), the largest, most versatile, and most pharmaceutically important group of membrane proteins, has been impaired over the years by the limited understanding of the molecular mechanisms underlying their diverse functions. The overall goal of the work proposed in this grant application is to explore the extent to which advanced computational strategies using enhanced sampling methods can improve dynamic molecular models of GPCRs, and generate novel testable hypotheses of functional modulation to pursue rational drug design successfully.